Feature-based Attribution

Feature-Based Attribution is a malware attribution method that identifies the source or family of malicious software by analyzing specific technical or behavioral characteristics extracted from the code, thereby distinguishing it from other attribution approaches that rely on circumstantial or contextual evidence.

48

Publications

3.3K

Citations

192

Authors

85

Institutions

Publications per year

2017–2026

46

Authors

192

  1. SL
    Su‐In Lee

    University of Washington, United States

    5 publications · 556 citations

    5

    h-index

  2. SL
    Scott Lundberg

    University of Washington, United States

    4 publications · 531 citations

    4

    h-index

  3. HC
    Hugh Chen

    University of Washington, United States

    3 publications · 474 citations

    3

    h-index

  4. JD
    Joseph D. Janizek

    University of Washington, United States

    3 publications · 119 citations

    3

    h-index

  5. GV
    Guy Van den Broeck

    KU Leuven, Belgium

    2 publications · 475 citations

    2

    h-index

1–5 of 192

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 1K citations

    12

    h-index

  2. 2

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 124 citations

    2

    h-index

  4. Journal of Hydrology

    1 publications · 15 citations

    1

    h-index

  5. 1

    h-index

1–5